Estimating Multiple Change Points in Multistage Processes

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Barati, Behzad | 2013

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 45969 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Akhavan-Niaki, Taghi
Abstract:
Control charts are considered as one of the most important tools of statistical process control in detection of assignable causes of variation in the processes. One of the main criticisms of these charts is their inability in discovering the out-of-control state in real time. To eliminate the main sources of error, indicating the actual time of deviation in processes which is called change point is very important. Diagnosing of real time of changes limits the range of search for the causes of deviations and maximizes the chance of finding the main sources of deviation resulting in time saving and reducing expenses. There are different types of change points. One of change point types which has been less studied is multiple change points. In this study an estimation of multiple change points in a multistage process is presented using artificial neural networks.A multistage process refers to processes which products are processed in more than one processing stage
Keywords:
Statistical Quality Control ; Artificial Neural Network ; Multistage Process ; Multiple Change Points

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